Our Approach with ZK

General Philosophy

ZK is not treated as base-layer infrastructure at Darklake. Darklake does not believe in generic or abstract ZK for its own sake, and instead takes a use case first approach. ZK is utilized it to solve specific problems, therefore avoiding unnecessary overhead and abstraction.

Case-by-case design

Each pool or product uses different ZK circuits and logic dependent on their specific needs. ZK is a precision tool optimized for each specific use-case individually. This allows us to maximise both speed and efficiency.

Comparison to L2 ZK approaches

Unlike Layer 2 solutions that operate off-chain and periodically post compressed proofs to a base layer, Darklake does not implement a rollup or L2 approach. It runs natively on Solana without outsourcing execution or state. Instead of batching or abstracting transactions, Darklake integrates zero-knowledge proofs directly into the execution path.

For the user this means:

• No batching delays - trades finalize and execute within a single block.

• Full composability and compatibility with the existing DeFi ecosystem - no need for bridging and new environments. All assets stay on Solana and transactions are immediately visible to other Solana programs.

• No additional trust assumptions - there’s no centralized sequencer, off-chain coordinator, or rollup verifier involved.

Darklake's objective isn't a full-stack privacy system, like Renegade. In order to provide complete trade privacy, Renegade's Dark Pools use an order book model and MPC-based matching. The trade-off is a complex infrastructure and additional latency in trade execution. Darklake on the other hand focuses on practical privacy - through an optimized AMM model to prevent MEV extraction within Solana's 400ms block time, while still maintaining the visibility of pool states.

In short, Darklake behaves like a standard AMM-based DEX, but with built-in MEV protection.